DBMS > Badger vs. BaseX vs. ITTIA vs. Teradata

System Properties Comparison Badger vs. BaseX vs. ITTIA vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Edge Time Series DBMS with Real-Time Stream Processing

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

github.com/dgraph-io/badger

basex.org

www.ittia.com

www.teradata.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.basex.org

docs.teradata.com

Developer

DGraph Labs

BaseX GmbH

ITTIA L.L.C.

Teradata

Initial release

2017

2007

1984

Current release

11.0, June 2024

8.7

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
Windows

hosted
Linux

Data scheme

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

XQuery supports types

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC
ODBC
RESTful HTTP API
WebSocket

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C++
JavaScript (Node.js)
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

multiple readers, single writer

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Database file passwords

fine grained access rights according to SQL-standard

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